@online{1,
	author = {Coppelia Robotics},
	title = {V-REP},
	month = {1},
	year = {2019, Accessed 14.01.2019},
	url = {http://www.coppeliarobotics.com/}
}
@online{2,
	author = {Coppelia Robotics},
	title = {ROS Melodic Morenia},
	month = {1},
	year = {2019, Accessed 14.01.2019},	
	url = {http://www.ros.org/about-ros/}	
}
@online{3,
	author = {HiBot Corporation},
	title = {ACM-R5H},
	month = 1,
	year = {2019, Accessed 14.01.2019},
	url = {https://www.hibot.co.jp/ecommerce/prod-detail/14}	
}
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booktitle={2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, 
title={Towards autonomous locomotion: Slithering gait design of a snake-like robot for target observation and tracking}, 
year={2017}, 
volume={}, 
number={}, 
pages={2698-2703}, 
keywords={gait analysis;mobile robots;motion control;path planning;robot dynamics;robot vision;stability;target tracking;velocity control;target observation;straight slithering gait;biased slithering gait;snake-like robot;slithering gait design;forward speed;stability;head composition algorithm;vision sensor;head module;autonomous locomotion scenarios;target tracking simulations;gait parameters;radius;Shape;Mathematical model;Three-dimensional displays;Head;Force;Robot sensing systems}, 
doi={10.1109/IROS.2017.8206095}, 
ISSN={2153-0866}, 
month={2.},}
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year={2008}, 
volume={43}, 
number={2}, 
pages={566-576}, 
keywords={CMOS image sensors;latency asynchronous temporal contrast vision sensor;CMOS vision sensor;spike event;address-event representation;active continuous-time front-end logarithmic photoreceptor;self-timed switched-capacitor differencing circuit;chip power consumption;silicon retina;image sensor;bandwidth 3 kHz;power 23 mW;time 15 mus;size 0.35 mum;Delay;Layout;Sensor arrays;Lighting;Sensor phenomena and characterization;Bandwidth;Dynamic range;Streaming media;Reflectivity;Timing;Address-event representation (AER);asynchronous vision sensor;high-speed imaging;image sensors;machine vision;neural network hardware;neuromorphic circuit;robot vision systems;visual system;wide dynamic range imaging}, 
doi={10.1109/JSSC.2007.914337}, 
ISSN={0018-9200}, 
month={2},}
@online{6,
author = {iniVation AG},
title = {DVS128},
month = 1,
year = {2019, Accesed 14.01.2019},
url = {https://inivation.com/support/hardware/dvs128/},	
}
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author={J. Kaiser and J. C. V. Tieck and C. Hubschneider and P. Wolf and M. Weber and M. Hoff and A. Friedrich and K. Wojtasik and A. Roennau and R. Kohlhaas and R. Dillmann and J. M. Zöllner}, 
booktitle={2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)}, 
title={Towards a framework for end-to-end control of a simulated vehicle with spiking neural networks}, 
year={2016}, 
volume={}, 
number={}, 
pages={127-134}, 
keywords={automobiles;cameras;complex networks;feedforward neural nets;learning (artificial intelligence);mobile robots;end-to-end simulated vehicle control;spiking neural networks;rate-based neural networks;deep learning architectures;neurorobotics applications;neural self-driving vehicle applications;camera images;silicon retina;DVS;steering wheel decoder;vehicle end-to-end for lane following behavior;hand-crafted feature detectors;complex networks;Robot sensing systems;Voltage control;Brain modeling;Cameras;Biological neural networks}, 
doi={10.1109/SIMPAR.2016.7862386}, 
ISSN={}, 
month={12},}
@INPROCEEDINGS{8, 
author={Z. Bing and C. Meschede and K. Huang and G. Chen and F. Rohrbein and M. Akl and A. Knoll}, 
booktitle={2018 IEEE International Conference on Robotics and Automation (ICRA)}, 
title={End to End Learning of Spiking Neural Network Based on R-STDP for a Lane Keeping Vehicle}, 
year={2018}, 
volume={}, 
number={}, 
pages={1-8}, 
keywords={control engineering computing;learning (artificial intelligence);mobile robots;neural nets;road vehicles;robot vision;SLAM (robots);spiking neural network;lane keeping vehicle;mobile applications;mobile robot applications;reward-modulated spike-timing-dependent-plasticity;reinforcement learning;Pioneer robot;lane information;robot tasks control;end to end learning approach;R-STDP;SNNs training;neuromorphic vision sensor;lateral localization accuracy;Voltage control;Task analysis;Robot sensing systems;Training;Synapses;Neurons}, 
doi={10.1109/ICRA.2018.8460482}, 
ISSN={2577-087X}, 
month={5},}
@online{9,
	author = {NEST Initiative},
	title = {NEST Simulator},
	month = 1,
	year = {2019, Accesed 14.01.2019},
	url = {http://nest-simulator.org/}	
}
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	year={2017},
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keywords={collision avoidance;learning (artificial intelligence);mobile robots;neurocontrollers;trajectory control;biologically inspired reinforcement learning;mobile robot collision avoidance;reinforcement learning technique;Q-learning algorithms;spiking neural networks;SNN;biological neural circuits;mobile robot navigation;goal-directed collision avoidance;reward-modulated spike-timing dependent plasticity learning rule;A-RM-STDP rule;biologically plausible feedforward spiking neural network architecture;navigation trajectories;Collision avoidance;Robots;Learning (artificial intelligence);Neurons;Biological neural networks;Additives}, 
doi={10.1109/IJCNN.2017.7966242}, 
ISSN={2161-4407}, 
month={5},}

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keywords={laser beam applications;mobile robots;neurocontrollers;plasticity;sensors;sonar;walls;biologically inspired spiking neural network;robot control;control structure;biological system;dynamic synapses;short-term plasticity;long-term synaptic plasticity;temporal difference learning rule;Pioneer robot simulator;laser proximity sensor;sonar proximity sensor;wall-following task;mobile robot;Neurons;Neurotransmitters;Robot sensing systems;Biological system modeling;Dynamic synapses;self-organization;spiking neural network (SNN);temporal difference (TD) learning rule;Artificial Intelligence;Computer Simulation;Models, Neurological;Neural Networks (Computer);Neuronal Plasticity;Robotics}, 
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publisher = {Cornell University},
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author={E. Rohmer and S. P. N. Singh and M. Freese}, 
booktitle={2013 IEEE/RSJ International Conference on Intelligent Robots and Systems}, 
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number={}, 
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keywords={control engineering computing;digital simulation;robots;V-REP;versatile robot simulation framework;scalable robot simulation framework;robotics systems;portable simulation framework;flexible simulation framework;control techniques;simulation models;productivity;built-in functionality;rapid algorithm development;system verification;rapid prototyping;safety monitoring;remote monitoring;training;education;hardware control;factory automation simulation;Robots;Load modeling;Sensors;Shape;Joints;Hardware;Computational modeling}, 
doi={10.1109/IROS.2013.6696520}, 
ISSN={2153-0858}, 
month={11},}
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title={Transcriptomic and morphophysiological evidence for a specialized human cortical GABAergic cell type}, 
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@INPROCEEDINGS{36, 
author={Dhanya E and N. Pradhan and Sunitha R and A. Sreedevi}, 
booktitle={2015 International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)}, 
title={Analysis of the dynamic behaviour of a single Hodgkin-Huxley neuron model}, 
year={2015}, 
volume={}, 
number={}, 
pages={441-446}, 
keywords={bioelectric potentials;brain models;cellular biophysics;neural nets;neurophysiology;biological neural network;external stimulus;single HH neuron;action potentials;real-time environment;Simulink;central nervous system;mathematical modeling;single Hodgkin-Huxley neuron model;dynamic behaviour;Neurons;Mathematical model;Computational modeling;Biological system modeling;Sodium;Potassium;Biomembranes;Action potential;Hodgkin-Huxley Neuron;Neuron Modeling;Simulink}, 
doi={10.1109/ERECT.2015.7499056}, 
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ISSN={1521-9615}, 
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